Point: Exponential trends in technology make the future more —  not less — predictable.

Story: At the World Innovation Forum in June, Ray Kurzweil, inventor of the first CCD scanner and author of The Singularity is Near, talked about the ease of predicting the future by spotting and extrapolating exponential trends.  Although Gordon Moore uttered his famous Law around 1970, Kurzweil found that the exponential trends in computation and data transmission predate Moore’s Law by many decades.  Moore spoke of the rate of evolution of semiconductor chips, but the trend started in earlier generations of computing and communications technologies including mechanical relays, vacuum tubes, and the first transistorized devices.  Even wars and depressions failed to halt the exponential progress in performance.  Trends in miniaturization and mass production meant information technologies improved at a steady pace across the decades.

Kurzweil noted that many people don’t understand the basic math of exponential trends.  When the Human Genome project had sequenced only 1% of the genome after seven years of costly labor, many cited the lack of progress as evidence that the project was doomed.  Yet the sequencing project was riding an exponential trend in the performance DNA sequencing methods.  Instead of taking another seven years to sequence a second 1%, they reached it after only one year. Then they reached 4% in about another year, then 8%, 16%, and so on.  It took about as much time to sequence the last 99% as it took to sequence the first 1%.  That’s the nature of exponential trends — they seem to start glacially slowly but finish lightening fast.

This trend continues unabated.  Along with exponential performance improvement comes an exponential drop in cost and an exponential rise in use.  What once took a billion dollars per genome is now costing a few thousand dollars per genome. Soon, scientists expect to have one million human genomes sequenced.  If genome sequencing is cheap enough, it can be used on every person, every cancer cell, every agricultural product, every bacteria, every virus, and even every pet. As performance hits key thresholds or cost drops below key thresholds, new applications can arise at predictable times.

What makes the future predictable with exponential trends is that we can estimate the crossing points when something becomes good enough, cheap enough, or valued enough for widespread use and new applications. Search engines arose from both the growing demand for finding websites in the exponentially growing World Wide Web and the declining costs of computer servers needed to offer a “free” search engine. Likewise, social networking arose as connectivity costs dropped, connectivity increased, and computer prices dropped.  Kurzweil said we may not be able to predict which company will rise like Google or Facebook to dominate some new application, but we can predict that such an application will become feasible and then widespread due to the confluence of exponential trends.

Action:

• Watch for exponential trends in underlying technologies, in which performance steadily doubles every few years or so or prices continually drop every few years or so.
• Look for crossing points where the speed or cost of doing some task — that’s outrageously expensive or abysmally slow today —  becomes affordable and timely.
• Think about new applications that might be possible if something is cheap, fast, and widely available. What happens when everyone is online via a mobile device 24×7? What happens when everyone knows their DNA sequence?
• Convert problems that don’t seem to have exponential performance improvement trends (i.e., healthcare) into ones that do (i.e., genome sequencing, patient databases, mobile app-enabled health sensors, self-care social networking, virtual models of diseases, etc.)

Point: You may not be able to predict the future, but you can prepare for it by tracking early trends and staying open to disruptions.

Story: What will the web look like in 20 years? Stuart Miniman of the Office of the CTO at EMC Corporation asked me to contribute my thoughts on this, as part of EMC’s ON magazine celebration of the web’s 20th anniversary.

My predictions for 2030? I know that I don’t know, but I do follow some heuristics that are helpful regardless of which future materializes.

“You can’t predict the future,” said Google’s Eric Schmidt back in 1993 when he was president of Sun Technology Enterprises (a subsidiary of Sun Microsystems). “But you can estimate it.  Your estimations are based on understanding the model of technology.”  Schmidt’s mental model of technology involves looking at underlying drivers and expecting innovation from anywhere. “Don’t think your company is the best and will be the first to come with an innovation in your area.  That attitude will lead you to become blindsided.”

With that in mind, here are two trends I’ll be watching closely for emerging innovations:
* Geo-Spatial Data and Semantic Smarts

Consider these facts by Jeff Jonas, IBM Distinguished Engineer and Chief Scientist, Entity Analytic Solutions, IBM Software Group:

Mobile devices in America are generating something like 600 billion geo-spatially tagged transactions per day. Every call, text message, email and data transfer handled by your mobile device creates a transaction with your space-time coordinate, whether you have GPS or not. Every few minutes, it sends a heartbeat, creating a transaction whether you are using the phone or not.

The implications? Companies can use data analytics to learn unprecedented amounts of information on their customers (how far they travel, locations where they hang out, the people they hang out with). It may sound like big brother, but some consumers are already turning this into a big game and social lifestyle with the help of companies like Foursquare, Loopt, Brightkite, etc. There’ll be opportunities for companies to use this data combined with web-based data to serve their customers better.

With every device and service gathering more and more data and becoming more connected, systems will begin to “understand” the meaning of the data to give people what they want.  I don’t know if real AI will ever happen, but with all the available data, social tools, and clever people building clever companies, it seems that devices are going to act like they know the meaning behind the data and and take or suggestion actions to help you. For example, if your cellphone knows your calendar’s next appointment, your location, and gets the Tweets about the traffic jam on the highway, it can alert you to leave a little earlier or alert whomever you’re meeting that you’ll be late.

* Social/Distributed Decision-Making

Knowledge-intensive tasks such new product and service development will be aided by enterprise-wide collaboration systems with built-in voting, reputation systems, and predictive markets.  These concepts were envisioned by MIT Prof. Thomas W. Malone before the Web as we know it even existed. His publications, such as Computers, Networks and the Corporation, describe the organizational changes that networked computers would bring.

Tom Malone now heads the Center for Collective Intelligence at MIT. The center’s basic research question is:  How can people and computers be connected so that—collectively—they act more intelligently than any individuals, groups, or computers have ever done before?

I think one of the most powerful uses of the web in the future is for crowdsourcing and open innovation to tackle some of the world’s biggest problems.  Take, for example, that Innocentive just announced a GlobalGiveback Innovation Challenge Set to help solve some of the world’s water problems through open innovation. Other crowdsourcing platforms like ideas4all.com are enabling entrepreneurs to suggest product, service and business ideas to win funding.  The web will enable collaboration on a global scale that will let us marshal our creative energies to tackle global issues.

What do you think?

And, yes, whatever the future brings, there’ll be an app for that.

Action

• Look for things that are becoming ubiquitous but aren’t being used as much as they could be.
• Avoid self-centered attitudes about the future. Just because you don’t want to be tracked doesn’t mean others don’t want to be tracked or that someone won’t create a fun and rewarding reason to change your mind about tracking.
• Look for chocolate+peanut-butter combinations like geo-spatial data + semantics.
• Test out some crowdsourcing platforms (ideas4all.com is public and ongoing) to get a feel for how they work. Consider how you could apply them.

Sources:

EMC’s ON magazine: The Web at Twenty

Jeff Jonas: Your Movements Speak for Themselves

Eric Schmidt at the University of Colorado-Boulder, February 9, 1993